Many companies have adopted AI, and few have gotten everything it can deliver.
What is missing is continuous knowledge management: checking what AI produces, learning from use, and rethinking the work with the people who do it. This is what we call continuous knowledge.
A network of specialists across the United States, Europe and Brazil.
AI gets stuck in places that aren't technical. Or not only technical.
The report looked finished. The sources did not exist.
- TechnologyThe text mixes what was calculated with what was guessed, in the same tone.
- TechnologyNothing in the system separates a checked fact from generated text.
- CraftReviewing used to mean reading the argument. Now it means checking every source, and that time is not in the deadline.
- PeopleNobody wants to be the one who delays delivery to check.
- PeopleWe trusted a report because it took work to make. The work shrank; the trust stayed.
- Ethics and lawWhoever signs answers for sentences they did not write.
- StrategyThe goal was to deliver faster. Checking was not part of the goal.
In 2025, Deloitte delivered a report to the Australian government that cited works that do not exist and misquoted a court judgment; the corrected version disclosed the use of generative AI, and the firm repaid the final installment of the contract. The same year, a health workforce plan it prepared for the Canadian province of Newfoundland and Labrador contained academic citations that do not exist. In both cases, Deloitte said the corrections do not change the conclusions.
Each layer calls for a different kind of experience. That is why EXP³ is a network.
AI changes so much, and so fast, that no single specialty can keep up.
Making AI work inside a company takes people with long experience in different fields and, often, from different cultures: every solution has to fit the organizational culture of its country. That is why EXP³ is a network of specialists.
We are former founders, software engineers, architects and technologists, mathematicians, philosophers, ethicists and lawyers, writers, musicians and other creatives, all using generative AI intensively since it arrived.
A network, not an org chart.
Long careers in fields that rarely meet. Together, they cover the whole problem: technology, people, craft, ethics and law, strategy.
Four ways to work with us.
Projects
We come in where the problem is: assessing what is already running, diagnosing, proposing, designing workflows with the people who run them, or implementing. Semantic layer, ontologies and knowledge engines whose answers can be verified.
See projects →Continuous
The project ends and the questions keep coming. The network within reach: screening of what is new, conversations with specialists, mentoring and one case analyzed in depth every month.
Tell me more →Learning
For those who decide and those who build, starting from cases the market has already lived through, organized by the pain each one exposes.
See the learning program →Life After AI
Public conversations about life and work after AI, with guests from inside and outside the network.
Listen to the conversations →Auditable analytical intelligence
For a performance agency in Brazil, Mexico and the United States: whoever calculates does not write. A deterministic layer checks every fact before the AI writes, and every claim in the report has a traceable origin.
Read the case →BLIU: creative memory
A knowledge graph that holds years of notes and references from comedy writers, in use in their creative sessions. The AI provokes, questions and shifts perspective; the decision and the authorship remain human.
What we don't automate.
Moral judgment is never automated.
Decisions that affect people's lives call for a responsible human, someone who signs off on them.
Amplify people, never replace them.
Whoever uses what we build comes out more capable, not less.
Responsible AI, always.
Governance, risks and impacts weighed in every project, for people, for the business and for society.
Bring us a real problem and the conversation starts there.
No maze of forms. Tell us where it hurts, in your own words, and a person from the network will reply.
Received. A person from the network will read it and reply.